• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.3
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• pp.58-70
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• 2023

Based on the current state of safety management for small-scaled old buildings, this study identified problems and proposed improvement plans. The study investigated the current status of safety management based on relevant laws and government and financial portal data, as well as budget documents related to the targets of safety management, the organization responsible for safety management, and the budget required for organizational operation. As a result, the study revealed the problem of safety management blind spots for buildings that are not included in the legal safety inspection targets. It also identified difficulties in securing specialized personnel for the operation of local building safety centers and financial constraints for the operation of building safety special accounting. To address these issues, the study proposed measures such as expanding the scope of safety inspection targets for small-scaled old buildings to reduce safety management blind spots, improving compensation regulations for specialized personnel, setting a minimum ratio for enforcement fines to secure financial resources, and gradually adjusting building permit fees. The study aimed to contribute to improving the efficiency of safety management for small-scaled old buildings based on these proposed measures.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.2
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• pp.281-290
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• 2022

In Korea, the number of national facilities for which a safety inspection is mandatory is increasing, and a safer safety inspection method is needed. This study aimed to increase the efficiency of the bridge safety inspection by enabling rapid exterior inspection while securing the safety of inspectors by using drones to perform the safety inspections of bridges, which had mainly relied on visual inspections. For the research, the Youngjong Grand Bridge in Incheon was selected as a test bed and was divided into four parts: the warren truss, suspension bridge main cable, main tower, and pier. It was possible to establish a five-step standard procedure for drone safety inspections. The step-by-step contents of the standard procedure obtained as a result of this research are: Step 1, facility information collection and analysis, Step 2, analysis of vulnerable parts and drone flight planning, Step 3, drone photography and data processing, Step 4, condition evaluation by external inspection, Step 5, building of external inspection diagram and database. Therefore, if the safety inspections of civil engineering facilities including bridges are performed according to this standard procedure, it is expected that these inspection can be carried out more systematically and efficiently.

• Journal of Dental Rehabilitation and Applied Science
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• v.38 no.1
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• pp.34-41
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• 2022

Recently, digital technology and computer-aided design/computer-aided manufacturing (CAD/CAM) environment have changed the clinician treatment method in the fabrication of dentures. The denture manufacturing method with CAD/CAM technology simplifies the treatment and laboratory process to reduce the occurrence of errors and provides clinical efficiency and convenience. In this case, complete dentures were fabricated using stereolithography (SLA)-based 3D printing in patient with mandibular deviation. Recording base were produced in a digital model obtained with an intraoral scanner, and after recording a jaw relation in the occlusal rim, a definitive impression was obtained with polyvinyl siloxane impression material. In addition, facial scan data with occlusal rim was obtained so that it can be used as a reference in determination of the occlusal plane and in arrangement of artificial teeth during laboratory work. Artificial teeth were arranged through a CAD program, and a gingival festooning was performed. The definitive dentures were printed by SLA-based 3D printer using a Food and Drug Administration (FDA)-approved liquid photocurable resin. The denture showed adequate retention, support and stability, and results were satisfied functionally and aesthetically.

• Journal of Appropriate Technology
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• v.5 no.2
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• pp.70-81
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• 2019

The garment industry is one of the most labor-intensive manufacturing industries, with its sewing process relying almost entirely on manual labor. Its costs highly depend on the efficiency of this production line and thus is crucial to determine the production rate in real-time for line balancing. However, current production tracking methods are costly and make it difficult for many Small and Medium-sized Enterprises (SMEs) to implement them. As a result, their reliance on manual counting of finished products is both time consuming and prone to error, leading to high manufacturing costs and inefficiencies. In this paper, a production tracking system that uses the sewing machines' energy consumption data to track and count the total number of sewing tasks completed through Convolutional Neural Network (CNN) classifiers is proposed. This system was tested on two target sewing tasks, with a resulting maximum classification accuracy of 98.6%; all sewing tasks were detected. In the developing countries, the garment sewing industry is a very important industry, but the use of a lot of capital is very limited, such as applying expensive high technology to solve the above problem. Applied with the appropriate technology, this system is expected to be of great help to the garment industry in developing countries.

• Korea Trade Review
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• v.42 no.1
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• pp.283-301
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• 2017

As a consequence of the changed role and functions in port operations, the role of port hinterland has transformed to multi-functional logistic centre linking more efficiently elements of the supply chain. This paper analysed distribution centre selection factors in Busan new port hinterland, aiming to diagnose and evaluate the operational situations of port hinterland as multi-functional logistics centre. Based on a data collected from all 122 samples located in Busan new port hinterland, determinants for location competitiveness identified were: political support, market potentiality, infrastructure utilization, market niche, and connectivity. Comparing the difference between an importance and performance, it is revealed that the target port hinterland requires urgent improvement in political supports such as incentive programmes offered by host country, free trade system and related law, financial assistance in constructing distribution centers, and simplicity, ease and efficiency of administrative procedures. The results provide useful insights for establishing future improvement strategies and a strategic agenda to successfully respond to the demands of the companies located in port hinterlands and/or new customers those who want to move in.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.12
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• pp.871-879
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• 2017

The purpose of this study is to propose a Busan tourism industry in which the 2016 OECD Tourism policy and ICT convergence platform are applied. OECD proposed 3 policies to promote the tourism industry: First, to maintain the competitiveness of the tourism industry as well as improve its efficiency and sustainability, second, to establish a seamless traffic system, and third, to build a response to the sharing economy. Centering on the OECD's three policies, we propose the developmental possibilities of tourism in Busan. At the same time, we suggest the necessity to build an ICT convergence platform that will help foster the industry. In building an ICT convergence platform, we especially focus on the necessity of: 1. Sharing and creating experience-based interactive contents on the software side, and 2. Developing high quality user experience (UX) and providing a data analysis-based customized service on the hardware side. In addition, we insist on the establishment of the Tourism Promotion Agency for the continuous performance and management of Busan tourism industry. The study ultimately suggests that the construction of ICT convergence platform based on OECD tourism policy can result in the expected outcomes of high effects with low cost for both consumers and suppliers related to the tourism industry.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.85-100
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• 2023

Corporate ESG performance (environmental, social, and corporate governance) reflecting a company's strategic sustainability has emerged as one of the main factors in today's investment decisions. The traditional ESG performance rating process is largely performed in a qualitative and subjective manner based on the institution-specific criteria, entailing limitations in reliability, predictability, and timeliness when making investment decisions. This study attempted to predict the corporate ESG rating through automated machine learning based on quantitative and disclosed corporate financial information. Using 12 types (21,360 cases) of market-disclosed financial information and 1,780 ESG measures available through the Korea Institute of Corporate Governance and Sustainability during 2019 to 2021, we suggested a deep neural network prediction model. Our model yielded about 86% of accurate classification performance in predicting ESG rating, showing better performance than other comparative models. This study contributed the literature in a way that the model achieved relatively accurate ESG rating predictions through an automated process using quantitative and publicly available corporate financial information. In terms of practical implications, the general investors can benefit from the prediction accuracy and time efficiency of our proposed model with nominal cost. In addition, this study can be expanded by accumulating more Korean and international data and by developing a more robust and complex model in the future.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1951-1975
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• 2023

Recent advances in Cognitive Radio Networks (CRN) have elevated them to the status of a critical instrument for overcoming spectrum limits and achieving severe future wireless communication requirements. Collaborative spectrum sensing is presented for efficient channel selection because spectrum sensing is an essential part of CRNs. This study presents an innovative cooperative spectrum sensing (CSS) model that is built on the Firefly Algorithm (FA), as well as machine learning artificial neural networks (ANN). This system makes use of user grouping strategies to improve detection performance dramatically while lowering collaboration costs. Cooperative sensing wasn't used until after cognitive radio users had been correctly identified using energy data samples and an ANN model. Cooperative sensing strategies produce a user base that is either secure, requires less effort, or is faultless. The suggested method's purpose is to choose the best transmission channel. Clustering is utilized by the suggested ANN-FA model to reduce spectrum sensing inaccuracy. The transmission channel that has the highest weight is chosen by employing the method that has been provided for computing channel weight. The proposed ANN-FA model computes channel weight based on three sets of input parameters: PU utilization, CR count, and channel capacity. Using an improved evolutionary algorithm, the key principles of the ANN-FA scheme are optimized to boost the overall efficiency of the CRN channel selection technique. This study proposes the Artificial Neural Network with Firefly Algorithm (ANN-FA) for cognitive radio networks to overcome the obstacles. This proposed work focuses primarily on sensing the optimal secondary user channel and reducing the spectrum handoff delay in wireless networks. Several benchmark functions are utilized We analyze the efficacy of this innovative strategy by evaluating its performance. The performance of ANN-FA is 22.72 percent more robust and effective than that of the other metaheuristic algorithm, according to experimental findings. The proposed ANN-FA model is simulated using the NS2 simulator, The results are evaluated in terms of average interference ratio, spectrum opportunity utilization, three metrics are measured: packet delivery ratio (PDR), end-to-end delay, and end-to-average throughput for a variety of different CRs found in the network.

• Steel and Composite Structures
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• v.48 no.2
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• pp.207-233
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• 2023

Steel-concrete composite box girder bridges are widely used in the construction of highway and railway bridges both domestically and abroad due to their advantages of being light weight and having a large spanning ability and very large torsional rigidity. Composite box girder bridges exhibit the effects of shear lag, restrained torsion, distortion and interface bidirectional slip under various loads during operation. As one of the most commonly used calculation tools in bridge engineering analysis, one-dimensional models offer the advantages of high calculation efficiency and strong stability. Currently, research on the one-dimensional model of composite beams mainly focuses on simulating interface longitudinal slip and the shear lag effect. There are relatively few studies on the one-dimensional model which can consider the effects of restrained torsion, distortion and interface transverse slip. Additionally, there are few studies on vehicle-bridge integrated systems where a one-dimensional model is used as a tool that only considers the calculations of natural frequency, mode and moving load conditions to study the dynamic response of composite beams. Some scholars have established a dynamic analysis model of a coupled composite beam bridge-train system, but where the composite beam is only simulated using a Euler beam or Timoshenko beam. As a result, it is impossible to comprehensively consider multiple complex force effects, such as shear lag, restrained torsion, distortion and interface bidirectional slip of composite beams. In this paper, a 27 DOF vehicle rigid body model is used to simulate train operation. A two-node 26 DOF finite beam element with composed box beams considering the effects of shear lag, restrained torsion, distortion and interface bidirectional slip is proposed. The dynamic analysis model of the coupled composite box girder bridge-train system is constructed based on the wheel-rail contact relationship of vertical close-fitting and lateral linear creeping slip. Furthermore, the accuracy of the dynamic analysis model is verified via the measured dynamic response data of a practical composite box girder bridge. Finally, the dynamic analysis model is applied in order to study the influence of various mechanical effects on the dynamic performance of the vehicle-bridge system.

• The Journal of Bigdata
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• v.7 no.1
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• pp.213-224
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• 2022

In logistics and distribution, Market Basket Analysis (MBA) is used as an important means to analyze the correlation between major sales products and to increase internal operational efficiency. In particular, the results of market basket analysis are used as important reference data for decision-making processes such as product purchase prediction, product recommendation, and product display structure in stores. With the recent development of e-commerce, the number of items handled by a single distribution and logistics company has rapidly increased, And the existing analytical methods such as Apriori and FP-Growth have slowed down due to the exponential increase in the amount of calculation and applied to actual business. There is a limit to examining important association rules to overcome this limitation, In this study, at the Main-Category level, which is the highest classification system of products, the utility item set mining technique that can consider the sales volume of products together was used to first select a group of products mainly sold together. Then, at the sub-category level, the types of products sold together were identified using FP-Growth. By using this sequential layer filtering technique, it may be possible to reduce the unnecessary calculations and to find practically usable rules for enhancing the effectiveness and profitability.